Image credit: Unsplash.
AI is changing how construction companies operate, helping them better manage data.
Modern construction projects are data-intensive, yet despite the sheer data available, budget overruns remain stubbornly common. From gaps in pre-construction planning and procurement workflows to fragmented reporting, it can be no small feat to manage costs over the course of a long project.
Today, more construction companies are embracing artificial intelligence tools that enable their teams to connect previously disconnected datasets, identify risks early, and automate manual workflows that otherwise cause delays and added costs.
Why Budget Overruns Remain So Frequent
Simply put, modern construction projects are complex, with many variables to account for. There may be inaccurate cost estimates in cases where early estimates were based on incomplete designs or on material prices for steel, lumber, or concrete that have since fluctuated. Scope creep is common, especially as owners often request design changes after construction begins.
Even changes that may seem small to an owner can have a ripple effect on labor and scheduling. Supply chain disruptions can make materials more expensive or harder to obtain. Labor shortages and understaffing can affect the final cost of a project, as can weather delays or unexpected site conditions, such as hidden underground utilities or poor soil; sometimes, renovations uncover structural problems that were previously invisible.
The day-to-day work of project management can present its own challenges, including unrealistic schedules or inefficient communication between contractors. Mistakes can require costly rework.
How AI Might Be Making a Difference
It is axiomatic that the problem with having too much data is having too much data. Some construction firms and their consultants are starting to use centralized AI workspaces to sort, aggregate, and query large datasets to avoid potential project delays.
“AI can basically scan the whole project and see what is necessary to finish first,” explains Vladimir Krstić, the founder and CEO of one such AI platform, Intrascope. “We can work with a lot of data, a lot of documents, and see priorities, maybe better than managers.”
One thing AI models are adept at doing is pulling together information from many different files. For example, a construction consultant might need to review numbers from vendor documents and written compliance standards; agentic AI can pull this data together and summarize it.
“There is a lot of documentation,” Krstić notes. “Everything is separated. You need to combine many sources to generate one report for one project.”
Doing that allows construction executives to spot more problems in advance. According to Krstić, “a man can read something and forget some parts. AI can analyze a lot of documents and it has learned from other documents and other use cases. So it can predict something that a man can overlook.”
For entrepreneurs like Vladimir Krstić, the goal isn’t to replace the construction workforce but to augment it by scanning entire project scopes to help prioritization, supporting procurement by identifying additional vendor sources, and compiling financial summaries from fragmented project updates.
Solving the Messy Middle
Meanwhile, other suppliers of AI platforms are addressing what MDI Cloud CTO Damien Baker calls the “messy middle,” meaning the compliance checks, inspection forms, and approval workflows that sit between a construction company’s ERP system and its delivery system. These manual processes, conducted on paper, are easy to neglect, but they are often the source of delays and cost overruns.
AI-first platforms like MDI Cloud digitize these middle workflows and automate compliance scheduling. The platform escalates exceptions to site managers in real time and maintains a full audit trail.
According to Baker, one MDI Cloud client was able to cut approximately 300 hours of labor per month in this way.
“We will always put a human in the loop to do a final review,” Baker adds, noting that human oversight of the automated process remains crucial to prevent hallucinations and to ask questions that a machine might not think to.
The Changing Shape of Construction
As AI tools become both more pervasive and more capable, they could present competitive advantages for construction companies that seek them out. Whether that means using intelligent workspaces to analyze project data or automating checks and compliance workflows that currently are completed on paper, AI-first firms are creating teams of AI models that could add value across the construction build cycle.
A consistent theme that emerges from conversations with the founders of these new firms is that they aren’t striving to replace existing teams but to empower construction teams to work smarter, catch problems earlier, and keep increasingly intricate projects on time and on budget.
